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Margin variations in support vector regression for the stock market prediction.

Yang, Haiqin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 98-109). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Time Series Prediction and Its Problems --- p.1 / Chapter 1.2 --- Major Contributions --- p.2 / Chapter 1.3 --- Thesis Organization --- p.3 / Chapter 1.4 --- Notation --- p.4 / Chapter 2 --- Literature Review --- p.5 / Chapter 2.1 --- Framework --- p.6 / Chapter 2.1.1 --- Data Processing --- p.8 / Chapter 2.1.2 --- Model Building --- p.10 / Chapter 2.1.3 --- Forecasting Procedure --- p.12 / Chapter 2.2 --- Model Descriptions --- p.13 / Chapter 2.2.1 --- Linear Models --- p.15 / Chapter 2.2.2 --- Non-linear Models --- p.17 / Chapter 2.2.3 --- ARMA Models --- p.21 / Chapter 2.2.4 --- Support Vector Machines --- p.23 / Chapter 3 --- Support Vector Regression --- p.27 / Chapter 3.1 --- Regression Problem --- p.27 / Chapter 3.2 --- Loss Function --- p.29 / Chapter 3.3 --- Kernel Function --- p.34 / Chapter 3.4 --- Relation to Other Models --- p.36 / Chapter 3.4.1 --- Relation to Support Vector Classification --- p.36 / Chapter 3.4.2 --- Relation to Ridge Regression --- p.38 / Chapter 3.4.3 --- Relation to Radial Basis Function --- p.40 / Chapter 3.5 --- Implemented Algorithms --- p.40 / Chapter 4 --- Margins in Support Vector Regression --- p.46 / Chapter 4.1 --- Problem --- p.47 / Chapter 4.2 --- General ε-insensitive Loss Function --- p.48 / Chapter 4.3 --- Accuracy Metrics and Risk Measures --- p.52 / Chapter 5 --- Margin Variation --- p.55 / Chapter 5.1 --- Non-fixed Margin Cases --- p.55 / Chapter 5.1.1 --- Momentum --- p.55 / Chapter 5.1.2 --- GARCH --- p.57 / Chapter 5.2 --- Experiments --- p.58 / Chapter 5.2.1 --- Momentum --- p.58 / Chapter 5.2.2 --- GARCH --- p.65 / Chapter 5.3 --- Discussions --- p.72 / Chapter 6 --- Relation between Downside Risk and Asymmetrical Margin Settings --- p.77 / Chapter 6.1 --- Mathematical Derivation --- p.77 / Chapter 6.2 --- Algorithm --- p.81 / Chapter 6.3 --- Experiments --- p.83 / Chapter 6.4 --- Discussions --- p.86 / Chapter 7 --- Conclusion --- p.92 / Chapter A --- Basic Results for Solving SVR --- p.94 / Chapter A.1 --- Dual Theory --- p.94 / Chapter A.2 --- Standard Method to Solve SVR --- p.96 / Bibliography --- p.98

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324265
Date January 2003
ContributorsYang, Haiqin., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xiii, 109 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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